Analytics Engineer

Location: New York, NY
Job Type: Engineering

IQ Workforce is a leading recruiting firm for the engineering, analytics, and data science communities.

One of our new clients is a SaaS marketplace start-up that provides licensed cannabis dispensaries the ability to order from their favorite brands, as well as a suite of software tools for those brands to manage their operations and scale. With 4,400+ dispensaries and 1,400+ leading brands in 25 states and territories, the company is setting the industry standard for how cannabis brands and retailers work together.

The company is currently seeking a pair of Analytics Engineers to join their newly formed Data & Analytics team.

The Analytics Engineer will possess a blend of a sharp analytical mindset and ability to implement analytics solutions that scale. You will be working across the data stack spectrum: creating reporting products by translating business questions into analytics requirements and also creating data sources from the warehouse to automate the pipeline. You will be presenting recommendations to business stakeholders from prototyped reporting products while also diving into the backend and writing code to scale the prototype. The ideal candidate should be personable, efficient, rooted in an experimentative and fact-based mindset. Bringing people along, communicating and gathering feedback on plans with internal and external stakeholders and collaborating cross-functionally should come easily to the candidate.

Responsibilities include:
Building processes and code bases for reporting pipelines using BI tools and modular code

Creating and migrating ad-hoc reporting and analysis to automated always-on reporting

Convert raw data into consumable information applying business logic and utilizing clean engineering workflows

Custodian of quality of final source of truth data being served to business users

Undertaking business analysis requiring inferential statistics

Interacting with stakeholders to understand and document business questions in-depth and propose optimum reporting solutions using standard frameworks

Expert level skills in writing optimized SQL for creating, updating and querying tables

Expert level skills in using Python for data processing and analysis at scale

Experience using Pandas, NumPy, Sci-Py is a must-have

Experience with multi-processing and Dask are a plus

Expert level skills in building reporting products using BI tools like Periscope, Tableau, Looker etc.

Experience working in modern data stack environment (preferably built on AWS)

Experience writing and packaging modular code to run as containers (Docker)

Experience using statistical inference to perform business analysis

Well-versed in version control systems (Git)

Exposure to dbt, Luigi, Airflow or other DAG based workflow frameworks

Comfortable working in a fast-paced growth business with many collaborators

Comfortable working across the stack when need arises